| import gradio as gr | |
| from transformers import pipeline | |
| def generate_story(story): | |
| ner = pipeline("ner", model="dbmdz/bert-large-cased-finetuned-conll03-english") | |
| return str(ner(story)) | |
| demo = gr.Interface ( | |
| fn=generate_story, | |
| description="Named Entity Recognition Demo with BERT (dbmdz/bert-large-cased-finetuned-conll03-english)", | |
| examples=[ | |
| ["England won the 2019 world cup vs The 2019 world cup happened in England."], | |
| ["Washington is the capital of the US vs The first president of the US was Washington."], | |
| ["My name is Ganesh Kamath and I work at AMD in Bangalore."] | |
| ], | |
| inputs=[gr.Textbox(lines=7, label="Text")], | |
| outputs=[gr.Textbox(lines=7, label="Story NER")] | |
| ) | |
| demo.launch(share=True) |